KFPCA: Kendall Functional Principal Component Analysis
Implementation for Kendall functional principal component analysis. Kendall functional principal component analysis is a robust functional principal component analysis technique for non-Gaussian functional/longitudinal data. The crucial function of this package is KFPCA() and KFPCA_reg(). Moreover, least square estimates of functional principal component scores are also provided. Refer to Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <arXiv:2102.01286>. Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <doi:10.1016/j.jmva.2021.104864>.
| Version: |
2.0 |
| Depends: |
R (≥ 2.10) |
| Imports: |
kader, utils, pracma, fdapace, fda, stats, graphics |
| Published: |
2022-02-04 |
| Author: |
Rou Zhong [aut, cre],
Jingxiao Zhang [aut] |
| Maintainer: |
Rou Zhong <zhong_rou at 163.com> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
no |
| CRAN checks: |
KFPCA results |
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